Parameter estimation from multiresponse data

Multiresponse data are familiar outputs of experiments and processes involving multicomponent mixtures, multiple streams or multiple methods of observation. The resulting arrays of data exhibit various structures, including rectangular (no missing values), block‐rectangular, and irregular (missing v...

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Bibliographic Details
Published in:AIChE journal 1992-05, Vol.38 (5), p.641-650
Main Authors: Stewart, Warren E., Caracotsios, Mike, Sørensen, Jan P.
Format: Article
Language:English
Subjects:
Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
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Summary:Multiresponse data are familiar outputs of experiments and processes involving multicomponent mixtures, multiple streams or multiple methods of observation. The resulting arrays of data exhibit various structures, including rectangular (no missing values), block‐rectangular, and irregular (missing values with no simple pattern). Methods for modeling such data are described, emphasizing parameter estimation strategy and available software. Experiences in multiresponse modeling are then reviewed for several chemical engineering problems.
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.690380502